With renewed interest in the development of civil supersonic aircraft, their return in the future is becoming more ever more likely. The environmental impact of emissions in the stratosphere on climate and the ozone layer therefore needs to be explored. The stratospheric ozone levels determine the amount of harmful ultraviolet radiation reaching the Earth's surface and thus the level of risk to human health and ecosystems. Ozone response is complex, varying with emission altitude and latitude and we are currently reliant on computationally expensive chemistry-transport models to calculate chemical species concentration changes resulting from supersonic aviation emissions. This paper takes a novel approach to reduce the dependency on these models, creating data-driven dynamical systems that model the global spatiotemporal atmospheric ozone response for different emission scenarios. The dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) methods are applied to atmospheric ozone data obtained from the GEOS-Chem model, and the evolution of the dominant POD spatial modes are modelled using sparse identification of nonlinear dynamics algorithm (SINDy). We show that DMD models can reconstruct monthly global column ozone changes with root mean square errors less than 0.05 Dobson unit (DU) for a period of three years. Predicting the global mean column ozone changes for the years beyond the period used to construct the models, results in errors less than 0.12 DU. Independent DMD models at two different altitudes can be interpolated to produce estimates for ozone response at an intermediate altitude. These methods can serve as a basis for low dimensional surrogate models that can be used to evaluate chemical species concentrations changes as a result of supersonic aviation emissions.

Minimisation of the climate impact of flights in the short term may be achieved by contrail avoidance. This involves avoiding ice supersaturated regions (ISSRs), which cause contrails to persist. ISSRs occur when the relative humidity over ice is above 1, but numerical weather prediction (NWP) models struggle to predict such regions. Below 235.15 K, solely ice supersaturation can be considered. This study validates the prediction of ISSRs in the ERA5 reanalysis using IAGOS in-situ measurements from a pressure level (350 to 175 hPa), seasonal, yearly (2011 to 2022) and regional perspective. Validation of ERA5’s temperature showed a cold bias in all extratropic regions and at low altitudes in the tropics, which can result in ERA5 predicting ISSRs when none are observed. Increasing temperature deviations between IAGOS and ERA5 were observed between the years 2020 and 2022. In terms of relative humidity over ice, ERA5 and IAGOS showed good agreement below ice supersaturation, but ERA5 struggled in simulating values close to or above a value of 1. For the latter conditions, ERA5 showed a dry bias in the extratropics below the tropopause. A moist bias was found in some regions and seasons, including South Asia, in June, July, and August. This may be due to inconsistencies in the modelling of the atmospheric ice content in ERA5. Years 2013 and 2014 also showed a possibility of a moist bias in ERA5 in some regions, but this was most likely the result of regional changes in sampling by IAGOS. The moist bias caused false detection of ISSRs in ERA5. Meanwhile, the dry bias led to an underestimation of the occurrence of ISSRs, with 25 to 50% remaining undetected. This causes an overestimation of no persistent contrail regions and an underestimation of persistent contrail and reservoir regions. When ERA5 overestimates the ISSR occurrence, it leads to an overestimation of persistent contrail and reservoir regions but an underestimation of no persistent contrail regions. Hence, improvements are necessary to successfully avoid or ensure unnecessary avoidance of ISSRs, where the latter could cause an increase in the climate impact of flights. Improvements should be done before implementation in contrail avoidance strategies, otherwise the benefit of such strategies may be defeated.